6D AI-Native Intelligence · StratIQX

Everyone reads the headline.
Nobody maps the cascade.

The 6D Foraging Methodology™ traces how a single business event propagates across six dimensions simultaneously — revealing what individual reporting misses and what strategy teams need to act on.

Every analysis ships reproducible source code — written in CAL.
272 cases published·148+ sectors·6/6 dimensions·days, not months
01 — The Gap

Standard analysis catches one dimension. Cascades move through six.

In February 2026, a five-minute Anthropic blog post erased $28 billion from IBM, Accenture, and Cognizant. The news cycle covered the AI announcement. What it missed: 60 years of accumulated complexity being repriced in real time — propagating simultaneously through customer contracts, employee positioning, revenue architecture, regulatory surface area, service quality assumptions, and operational dependencies.

In December 2025, four major entertainment studios began restructuring simultaneously. Individual merger reviews passed their respective regulators. No single body was tracking the aggregate: $82.7 billion in deals, 17,000 jobs cut, and a sector-wide consolidation that every dimension of the industry was absorbing at once.

This is the gap that 6D Intelligence fills. Not faster news. Not more data. A structured framework for tracing how an event moves through an organization or sector — all six dimensions, scored and sequenced — so that strategy teams, analysts, and editors see the full cascade, not just the trigger.

“The individual events fall below any single threshold — which is precisely why the aggregate view matters.”

— From UC-015, Peak TV Unpeaked · February 2026
02 — Recent Analyses

From the case library

UC-272

The Clock on the Live Proof

The AI-in-Finance cluster capstone. A validated-in-simulation JPMorgan AI allocation system, a named-but-unmaterialized systemic convergence risk, a regulator that withdrew its own rulemaking, and a dated EU enforcement deadline days away — four independent, dated questions. This case refuses to guess which resolves first, and scoreboards all four instead. Reviewed July 11, 2027. FETCH 1,780.

UC-270

The Backtest Can’t See What Hasn’t Happened Yet

JPMorgan built 8 AI agents that beat a 60/40 portfolio by 0.7 points a year in a 20-year backtest — outperforming even the firm’s own existing model. JPMorgan itself says this proves nothing about live performance, and no comparable fund anywhere has a verified live track record either. The opening case of the AI-in-Finance cluster. FETCH 2,861.

UC-250

The “F U” Cascade IV

For years the book on Carolina was fixed: a defense-first system, total buy-in, no superstar — and therefore no championship. In 2026 they beat the Vegas Golden Knights 4-2 for the Stanley Cup — the NHL’s purest star-aggregation machine (Eichel, Stone, Pietrangelo, cap-maxed, LTIR-maneuvered) beaten by its purest culture-and-development team. The Conn Smythe went to Jordan Staal, a defensive culture captain; the coach, Brind’Amour, was the captain who won in 2006. The fourth “F U” Cascade — the first three showed identity outpacing capital in the standings; this one wins the Cup head-to-head. FETCH 2,742.

UC-249

The Upstream Migration

For fifty years software discipline has done one thing: move the definition of “correct” one layer earlier, each time the cost of being wrong arrived sooner. The 1968 software crisis forced structure; TDD (2002–03) pinned correctness at implementation, DDD (2003) at the domain, BDD (2006, built on DDD) at behaviour. AI agents collapse the design-to-production gap to near zero — so the next move is governance, before the agent runs. That is GDD: the latest instance of the oldest pattern, already running in production. FETCH 3,116.

UC-248

The Foundation Dividend

In 1986 Canada reached the World Cup with real talent, scored zero goals, and vanished for 36 years — “an era of great talent that amounted to nothing.” In 2026 it reached its first-ever knockout round. The variable was never the talent — it was the development foundation built in the gap: an aligned youth-to-senior pyramid, province-wide scouting, and a $7M/yr academy network on a 10-year horizon. 1986 had the fish. 2026 built the dam. FETCH 2,662.

Browse all 272 cases in the library →
03 — How It Works

From trigger event to published intelligence

STEP 01

Trigger Event

A merger announcement, earnings surprise, AI disruption, policy shift, or sector-wide signal is identified as a cascade candidate — proactively or by request.

STEP 02

6D Analysis

Each of the six dimensions is assessed for activation, scored for severity, and sequenced into a cascade chain with sourced evidence and FETCH scoring.

STEP 03

Published Intelligence

Structured output delivered as a case analysis — cascade-chained, scored, and source-cited. Formatted to your specification or published to the library.

Typical turnaround: 24–72 hours for standard engagements. Same-day output available for time-sensitive situations.
See the full 8-stage pipeline →

The headline is the trigger. The cascade is the story.

One conversation. We'll tell you if the six-dimensional view adds something new — or confirm your current tools have it covered.

Lineage

Structured input. Generated output. Auditable artifacts.

The 6D Foraging Methodology™ and CAL were created by a founding contributor to .netTiers (2005–2010), one of the earliest schema-driven code generation frameworks for .NET. The pattern spans 21 years: define the structure once, generate the output deterministically, make every step traceable. In 2005, the input was a database schema. In 2026, the input is a business event and the output is a six-dimensional cascade analysis with reproducible source code written in CAL.

10 DOIs published · npm runtime · 272+ cases · 148+ sectors · 21 years of structured generation